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lscsoft-glue

LSCSoft-GLUE is a collection of utilities for running data analysis pipelines for online and offline analysis as well as accessing various grid utilities.

With conditionsPyPI PhysicsReleased Jul 202588.4K downloads / moGPL-2.0-or-laterPure Python

Decision gist · record as of 2026-08-14

pure-Python wheel — lscsoft_glue-4.1.1-py3-none-any.whl
v4.1.1 · released 2025-07-18 · Python >=3.6 · 1 runtime deps: igwn-segments

Yes, if you are working with LIGO data or gravitational-wave physics research and need grid pipeline infrastructure. The low install friction, broad Python version support, and stable classifier make it straightforward to adopt. However, the aging maintenance status (last release 392 days ago) means you should verify that it still meets your current grid infrastructure and Python environment before committing to a production workflow.AI-flagged interpretation of the facts on this page — verify before relying

Before you install

  • Requires Python 3.6 or later; designed for POSIX systems.
  • Low install friction with a single runtime dependency (igwn-segments).
  • Last release was 392 days ago; maintenance status is aging, so expect infrequent updates.

License · maintenance · safety

GPL-2.0-or-later (copyleft) — Distributed under GPL-2.0-or-later (copyleft). Any derivative work or distribution must also be open-source under a compatible license.

last release 2025-07-18 (392 days)

0 known vulnerabilities (OSV.dev, 2026-08-14) · 88,406 downloads/mo, #13,731 on PyPI

Verify before relying

pip install lscsoft-glue

import glue
# Access grid utilities and pipeline tools from the glue module
  • Whether igwn-segments is a compiled dependency or has system-level requirements beyond Python.
  • Specific grid infrastructure or credentials needed to use grid utilities beyond basic import.
  • Whether the 392-day gap since last release reflects stable maintenance or active abandonment.
Same gist for agents: .md · .json

What it is and what it does

LSCSoft-GLUE is a toolkit built for the LIGO Scientific Collaboration to support gravitational-wave data analysis. It bundles utilities for constructing and running analysis pipelines—both real-time online processing and batch offline analysis—along with interfaces to grid computing resources commonly used in physics research. The package is stable (Production/Stable classifier) and supports Python 3.6 through 3.13.

The package is designed for researchers and engineers working with LIGO data or similar large-scale physics experiments. It abstracts away grid submission, data access, and pipeline orchestration details so that analysts can focus on the science. Its single runtime dependency (igwn-segments) keeps the installation lightweight. The copyleft GPL-2.0-or-later license means any modifications or redistributions must remain open-source.

Use it for

  • Construct and submit gravitational-wave data analysis pipelines to grid computing clusters.
  • Access and manage time-segment metadata for LIGO detector data in offline analysis workflows.
  • Automate batch processing of large physics datasets across distributed computing infrastructure.
  • Integrate grid job submission and monitoring into custom Python analysis scripts.
  • Manage online real-time data analysis pipelines for detector monitoring or alert generation.

Worth the install?

AI-flagged interpretation of the facts on this page. Verify before relying on it.

With conditions

Yes, if you are working with LIGO data or gravitational-wave physics research and need grid pipeline infrastructure.

The low install friction, broad Python version support, and stable classifier make it straightforward to adopt. However, the aging maintenance status (last release 392 days ago) means you should verify that it still meets your current grid infrastructure and Python environment before committing to a production workflow.

Install

lscsoft-glue on PyPI

Before you install

Low install friction with a single runtime dependency (igwn-segments). Last release was 392 days ago; maintenance status is aging, so expect infrequent updates.

Requires Python 3.6 or later; designed for POSIX systems.

License in practice

Distributed under GPL-2.0-or-later (copyleft). Any derivative work or distribution must also be open-source under a compatible license.

Quickstart

pip install lscsoft-glue

import glue
# Access grid utilities and pipeline tools from the glue module

Verify before relying

  • Whether igwn-segments is a compiled dependency or has system-level requirements beyond Python.
  • Specific grid infrastructure or credentials needed to use grid utilities beyond basic import.
  • Whether the 392-day gap since last release reflects stable maintenance or active abandonment.

Package facts

LicenseGPL-2.0-or-later copyleft
Python supportSupports the current Python release >=3.6
Install frictionLow. Pure-Python wheel
Runtime dependencies
1 package
igwn-segments
MaintenanceAging 392 days since the last release
First released
Downloads88,406 / month, #13,731 on PyPI 30-day window, as of 2026-08-14
Known vulnerabilitiesNone known OSV.dev, checked 2026-08-14
Classifiers
Development Status :: 5 - Production/StableIntended Audience :: Science/ResearchLicense :: OSI Approved :: GNU General Public License v2 or later (GPLv2+)Operating System :: POSIXProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.6Programming Language :: Python :: 3.7Programming Language :: Python :: 3.8Programming Language :: Python :: 3.9Topic :: Scientific/Engineering :: AstronomyTopic :: Scientific/Engineering :: Physics

Evidence: lscsoft_glue-4.1.1-py3-none-any.whl

Tags

Capabilities
gravitational wave data analysisligo pipeline utilitiesgrid computing for physicsdata analysis pipeline toolslsc user environmentoffline analysis frameworkscientific computing grid access
Topics
gravitational-wavegrid-computingligo-data

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See also lalsuite · igwn-ligolw · dttlib · igwn-segments · silx · awsglue-dev · google-compute-engine · power-grid-model · pulp-glue · dbt-glue